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Help & Documentation

About the Model

This advanced paragliding model provides detailed hyper local forecasts/simulations of flying conditions. It simulates crucial factors such as thermal activity, wind behavior, and terrain-induced effects, enabling pilots to make informed and safer decisions. The model operates at a fine 10m by 10m resolution, making it exceptionally precise for terrain-driven airflow simulations, Note: features smaller than 10m, such as individual trees or buildings, cannot be resolved.

Use Cases

What Does the Model Do?

• Wind Field Simulation: Predicts wind direction, speed, and deviations caused by terrain interactions. It includes detection of lift and sink zones, which are vital for flight planning. However, small-scale rotors behind houses or trees, and some larger scale rotors (like those frequently experienced at Mam Tor during Northeasterlies), are beyond its current scope due to resolution constraints.
• Thermal Prediction: Simulates realistic thermal particle release points based on solar heating, terrain slope, and wind influence. It identifies thermal hotspots and continuous versus pulsing thermal zones, optimizing flight planning for thermal flying.
• Solar Intensity Analysis: Calculates terrain-specific solar radiation intensity, influencing thermal generation and flying conditions throughout the day.
• Real-Time Mobile API: Offers a mobile-optimized interface specifically tailored for paragliding use. Users can interactively select various visualization layers, such as solar intensity, thermal triggers, and wind deviations.
• Comprehensive Database: Features detailed information on over 800 paragliding sites across the UK, enabling pilots to easily find and evaluate flying conditions at their preferred locations.

Data Sources

The model integrates the highest quality datasets currently available to provide accurate forecasts:

• Terrain Data: Utilizes the England and Wales 10m resolution LiDAR terrain data, ensuring high precision in elevation modeling.
• Land Classification: Employs Google's Dynamic World dataset for precise classification of land types (such as water, forest, grassland, urban areas, etc.), significantly enhancing the accuracy of thermal and wind interaction predictions.
• Meto Data: Polls the UK Met offices 2km high resolution short term forecast for wind strength and direction.

Model Limitations

• Due to its 10m resolution, the model does not identify small-scale terrain features or obstacles less than 10 meters in size, including individual houses, small buildings, or trees.
• Rotor turbulence created by small-scale obstacles or highly localized topographic variations may not be fully captured.
• Certain large-scale rotor phenomena, such as those observed in locations like Mam Tor under specific wind conditions (e.g., Northeasterlies), may also be underrepresented.

Our model is continually refined with new data and user feedback, aiming to provide pilots with the best tools to ensure enjoyable and safe flying experiences.

For any issues, please contact support@windsight.app.